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111 lines
3.6 KiB
C++
111 lines
3.6 KiB
C++
// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra.
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//
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// Copyright (C) 2008-2011 Gael Guennebaud <gael.guennebaud@inria.fr>
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//
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// This Source Code Form is subject to the terms of the Mozilla
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// Public License v. 2.0. If a copy of the MPL was not distributed
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// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
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#include "sparse.h"
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template<typename Scalar,typename Index> void sparse_vector(int rows, int cols)
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{
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double densityMat = (std::max)(8./(rows*cols), 0.01);
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double densityVec = (std::max)(8./float(rows), 0.1);
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typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
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typedef Matrix<Scalar,Dynamic,1> DenseVector;
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typedef SparseVector<Scalar,0,Index> SparseVectorType;
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typedef SparseMatrix<Scalar,0,Index> SparseMatrixType;
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Scalar eps = 1e-6;
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SparseMatrixType m1(rows,rows);
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SparseVectorType v1(rows), v2(rows), v3(rows);
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DenseMatrix refM1 = DenseMatrix::Zero(rows, rows);
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DenseVector refV1 = DenseVector::Random(rows),
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refV2 = DenseVector::Random(rows),
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refV3 = DenseVector::Random(rows);
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std::vector<int> zerocoords, nonzerocoords;
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initSparse<Scalar>(densityVec, refV1, v1, &zerocoords, &nonzerocoords);
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initSparse<Scalar>(densityMat, refM1, m1);
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initSparse<Scalar>(densityVec, refV2, v2);
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initSparse<Scalar>(densityVec, refV3, v3);
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Scalar s1 = internal::random<Scalar>();
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// test coeff and coeffRef
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for (unsigned int i=0; i<zerocoords.size(); ++i)
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{
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VERIFY_IS_MUCH_SMALLER_THAN( v1.coeff(zerocoords[i]), eps );
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//VERIFY_RAISES_ASSERT( v1.coeffRef(zerocoords[i]) = 5 );
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}
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{
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VERIFY(int(nonzerocoords.size()) == v1.nonZeros());
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int j=0;
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for (typename SparseVectorType::InnerIterator it(v1); it; ++it,++j)
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{
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VERIFY(nonzerocoords[j]==it.index());
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VERIFY(it.value()==v1.coeff(it.index()));
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VERIFY(it.value()==refV1.coeff(it.index()));
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}
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}
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VERIFY_IS_APPROX(v1, refV1);
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v1.coeffRef(nonzerocoords[0]) = Scalar(5);
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refV1.coeffRef(nonzerocoords[0]) = Scalar(5);
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VERIFY_IS_APPROX(v1, refV1);
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VERIFY_IS_APPROX(v1+v2, refV1+refV2);
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VERIFY_IS_APPROX(v1+v2+v3, refV1+refV2+refV3);
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VERIFY_IS_APPROX(v1*s1-v2, refV1*s1-refV2);
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VERIFY_IS_APPROX(v1*=s1, refV1*=s1);
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VERIFY_IS_APPROX(v1/=s1, refV1/=s1);
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VERIFY_IS_APPROX(v1+=v2, refV1+=refV2);
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VERIFY_IS_APPROX(v1-=v2, refV1-=refV2);
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VERIFY_IS_APPROX(v1.dot(v2), refV1.dot(refV2));
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VERIFY_IS_APPROX(v1.dot(refV2), refV1.dot(refV2));
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VERIFY_IS_APPROX(v1.dot(m1*v2), refV1.dot(refM1*refV2));
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int i = internal::random<int>(0,rows-1);
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VERIFY_IS_APPROX(v1.dot(m1.col(i)), refV1.dot(refM1.col(i)));
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VERIFY_IS_APPROX(v1.squaredNorm(), refV1.squaredNorm());
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VERIFY_IS_APPROX(v1.blueNorm(), refV1.blueNorm());
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// test aliasing
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VERIFY_IS_APPROX((v1 = -v1), (refV1 = -refV1));
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VERIFY_IS_APPROX((v1 = v1.transpose()), (refV1 = refV1.transpose().eval()));
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VERIFY_IS_APPROX((v1 += -v1), (refV1 += -refV1));
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// sparse matrix to sparse vector
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SparseMatrixType mv1;
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VERIFY_IS_APPROX((mv1=v1),v1);
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VERIFY_IS_APPROX(mv1,(v1=mv1));
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VERIFY_IS_APPROX(mv1,(v1=mv1.transpose()));
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// check copy to dense vector with transpose
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refV3.resize(0);
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VERIFY_IS_APPROX(refV3 = v1.transpose(),v1.toDense());
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VERIFY_IS_APPROX(DenseVector(v1),v1.toDense());
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}
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void test_sparse_vector()
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{
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for(int i = 0; i < g_repeat; i++) {
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CALL_SUBTEST_1(( sparse_vector<double,int>(8, 8) ));
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CALL_SUBTEST_2(( sparse_vector<std::complex<double>, int>(16, 16) ));
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CALL_SUBTEST_1(( sparse_vector<double,long int>(299, 535) ));
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CALL_SUBTEST_1(( sparse_vector<double,short>(299, 535) ));
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}
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}
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